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Related Experiment Video

Updated: Apr 16, 2026

Following the Dynamics of Structural Variants in Experimentally Evolved Populations

Following the Dynamics of Structural Variants in Experimentally Evolved Populations

Published on: February 3, 2023

Quantitative evolutionary dynamics using high-resolution lineage tracking.

Sasha F Levy¹, Jamie R Blundell², Sandeep Venkataram³

¹1] Department of Genetics, Stanford University, Stanford, California 94305-5120, USA [2] Laufer Center for Physical and Quantitative Biology, Stony Brook University, Stony Brook, New York 11794-5252, USA [3] Department of Biochemistry and Cellular Biology, Stony Brook University, Stony Brook, New York 11794-5215, USA.

|March 4, 2015

Summary

This summary is machine-generated.

Evolutionary dynamics in large asexual populations, often hidden, were revealed using high-resolution lineage tracking. Early adaptation is reproducible but later stages show variability due to mutation effects.

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Last Updated: Apr 16, 2026

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Published on: February 3, 2023

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Heuristic Mining of Hierarchical Genotypes and Accessory Genome Loci in Bacterial Populations

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Published on: December 7, 2021

Area of Science:

Evolutionary biology
Microbial genetics
Population dynamics

Background:

Asexual cell population evolution contributes to significant global mortality.
Understanding the dynamics of competing beneficial lineages is crucial but challenging.
Hidden evolutionary trajectories at low frequencies limit current knowledge.

Purpose of the Study:

To develop and utilize an ultra high-resolution lineage tracking system.
To investigate the spectrum of beneficial mutation fitness effects.
To elucidate the dynamics of early adaptation in asexual populations.

Main Methods:

Constructed a sequencing-based ultra high-resolution lineage tracking system.
Monitored relative frequencies of approximately 500,000 lineages simultaneously in Saccharomyces cerevisiae.
Analyzed the spectrum of fitness effects of beneficial mutations.

Main Results:

The spectrum of beneficial mutation fitness effects is neither exponential nor monotonic.
Early adaptation is predictable and reproducible, driven by initial small-effect mutations.
Rarer, large-effect mutations outcompete initial ones, leading to variability between replicates.

Conclusions:

Early evolutionary dynamics can be deterministic.
Stochastic effects become significant as adaptation progresses.
High-resolution lineage tracking reveals complex evolutionary trajectories.